JPH09179739A - Information processing system and method therefor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To retrieve more plentiful information by referring to mutual relation stored in a knowledge base and reading the knowledge of other items relating to a read value. SOLUTION: The knowledge structure P1 of a person is inputted (S471), and since an organization is present in a slot S7 and the value of the slot S7 is a pointer to the knowledge structure Org1 of the organization, the knowledge structure Org1 is retrieved (S472-473.) In the knowledge structure of the organization, since a place is in the slot S7 and the value of the slot S7 of the knowledge structure Org1 is the painter to the knowledge structure V2 of Venue, the knowledge structure V2 is retrieved and outputted (S474). That is, for a certain item, at the time of obtaining the value of the specified attribute of the item, the knowledge of the other item relating to the item is referred to from the knowledge base, the knowledge not directly described as the knowledge of the item is utilized as well and the retrieval of the more plentiful information is made possible for one item.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an information processing system and method for outputting a requested type of information by referring to a knowledge base on the basis of input information.

[0002]

2. Description of the Related Art Conventionally, a system for analyzing and inferring information by referring to a knowledge base has been devised.

[0003]

In such a system, various knowledges about a certain matter are stored in the knowledge base so that they can be referred to. Further, one matter is directly described as knowledge of the matter. It is desirable to conduct a search that also utilizes knowledge that is not available.

[0004]

According to the present invention, in an information processing system, a knowledge base for storing, as knowledge, the values of a plurality of predetermined attributes of each item, the category of each item, and the interrelationship between the categories. And a reading means for reading the value of the specified attribute of the item specified by the specifying means from the knowledge base, and the mutual relation stored in the knowledge base. And a control means for controlling the reading means so as to read the knowledge of other matters related to the value read by the reading means.

According to another aspect of the present invention, the information processing system has a knowledge base for storing, as knowledge, the values of a plurality of predetermined attributes of each item, the category of each item, and the interrelationship between the categories. A designation means for designating a plurality of matters; a reading means for referring to the mutual relationship with respect to each of the plurality of matters designated by the designation means to read knowledge about the relevant matters from the knowledge base; Determining means for determining the common part of the knowledge read by the reading means.

According to another aspect of the present invention, in the information processing method, a designation step of designating an item and an attribute and a value of a designated attribute of the item designated by the designating step are provided.
With reference to the reading step of reading from a knowledge base that stores the values of a plurality of predetermined attributes of each item, the category of each item, and the interrelationship between each category as knowledge, and the interrelationship stored in the knowledge base. , A control step of controlling the reading step so as to read knowledge of other matters related to the value read by the reading step.

According to another aspect of the present invention, in the information processing method, a specified step of specifying a plurality of items and a plurality of predetermined items of each item with respect to each of the plurality of items specified by the specified step. Reading the knowledge about the related matter from the knowledge base with reference to the mutual relation of the knowledge base that stores the value of the attribute of, the category of each matter, and the mutual relation between the categories as knowledge.
And a determining step of determining a common part of the knowledge read by the reading step.

[0008]

BRIEF DESCRIPTION OF THE DRAWINGS FIG.
A preferred embodiment according to the present invention will be described in detail.

FIG. 1 shows a natural language processing apparatus 1 according to the present invention.
It is a block diagram which shows the hardware constitutions of an Example.

In the figure, reference numeral 1 is an input unit for inputting information in natural language. In the following, this input information will be referred to as a sentence, but this device can be processed even if it is not a grammatically complete sentence as long as it has a certain regular structure. Reference numeral 2 denotes a CPU, which performs calculations for various processes, logical judgments, etc., and controls each component connected to the bus 6. An output unit 3 outputs information.

Reference numeral 4 denotes a program memory, which is a memory for storing a program for control by the CPU 2 including a processing procedure which will be described later with reference to a flowchart. The program memory 4 may be a ROM or a RAM loaded with a program from an external storage device or the like.

Reference numeral 5 denotes a data memory, which stores data generated by various processes and also stores knowledge of a knowledge base described later. The data memory 5 is, for example, a RAM, but the knowledge of the knowledge base is stored in a non-volatile external storage medium.
It should be loaded prior to processing, or referenced whenever necessary.

Reference numeral 6 denotes a bus for transferring an address signal indicating a component to be controlled by the CPU 1, a control signal for controlling each component, and a transfer of data exchanged between each component. is there.

FIG. 2 is a diagram showing the structure of the knowledge base 20, which is a world knowledge base WK.
B) 31, domain knowledge base D
KB) 32, a dictionary 33, and a database 34. WKB 31 has knowledge of general things. The DKB 32 has knowledge of a goal plan model and the like. The dictionary 33 is a linguistic knowledge base having a knowledge of a language equivalent to a normal dictionary.
The database 34 stores personal information and the like.

FIG. 3 is a diagram showing the contents of the general knowledge base 31. general world knowledge is (a) ~
It is classified as (g). FIG. 4 shows the (a) object (Physical) of FIG.
It is a figure which shows the structure of the concept of (object). An object consists of all the objects that physically exist in nature (weight),
It has dimensions and so on. Each object is associated with various features that uniquely characterize the object as shown in FIG. In the figure, for example, in the case of human being, "function" is survival, and "abstract value" is life in that case. Also, the "related abstract entity" is sunset in the case of the sun. The "property" includes countable, adjective modifiable, expendable resources, and destructible.

FIG. 5 is a diagram showing the main types of knowledge structure that exist below an object. Objects are roughly classified into two categories: life forms (all living things including plants) and non-life forms. Life forms are further classified into immovable ones and movable ones. Immovable items include plants, and movable items are classified into birds and animals. As shown in FIG. 5, humans are under animals.

Further, as shown in FIG. 5, the non-living body is further classified into a natural one and an artificial one, and the natural one moves with a movable one (sand, rock, water, etc.). It is classified as impossible (mountain, plain, sea, etc.). The latter is also derived from SPACE. In addition, artificial objects are classified into movable objects and immovable objects. Movable objects include dynamic objects (automobiles, airplanes, etc. that you can move by yourself), static objects (boxes, pens, etc. that can be lifted and carried), and intermediate objects (bicycles, etc.). Objects that move by themselves like objects and are easily lifted like static objects) are classified. Dynamic objects are classified into large vehicles such as airplanes and trains and small vehicles such as buses and cars.
Includes owner's slot.

The static objects are classified into money (having a slot of type of money (check or cash)), equipment / machine, editable items, written objects, and the like. Further, as shown in FIG. 6, the written material is classified into units (on one topic) and collections (on multiple topics). The unit has slots shown in a1) and subcategories shown in a2). Similarly, the collection has the slots shown in b1),
It has the subcategories shown in b2).

Further, the documents belonging to b2) are personal documents (letters, faxes, memos, etc.) and official documents (tickets, visas,
Passports, etc., public documents (timetable,
Public notice, advertisement, etc.) Each structure is c),
It is shown in d) and e).

Returning to FIG. 5, non-living, man-made immovable objects (buildings, bridges, etc.) are also guided from SPACE and have fixed positions. The building is also a public building (mainly for leisure,
Halls, museums, zoos, etc.), living buildings (hotels, restaurants, homes, etc.), functional buildings (offices, universities, airports, research institutes, etc.). Public buildings have slots for what is famous, living buildings have slots for who (or which organization) belongs,
And has a resident slot. Functional building is also guided by ORGANIZATION, so ORGA
Get NIZATION properties (function, business, address).

FIG. 7 is a diagram showing the structure of a person. As shown in the figure, the person inherits the slot of the name of the object, which is classified into a first name, a middle name, and a surname. Also, all life forms are
That is, it has a survival time since birth. Furthermore, the person
It has slots for telephone number, birthday, address, social status, organization, business (including current business, previous business, normal business, and other business), title, hobby, parent, child, etc. The lower part of FIG. 7 shows the structure of a person named Kono Gitaro.

FIG. 8 is a diagram showing a knowledge structure under the abstract existence. They have no physical presence, they exist only in the heart, thanks, thoughts, beauty, trips, fears,
Includes knowledge and skills such as physics and chemistry. The subcategory of abstract existence is M Place (Organization etc.) and Abstract Obj. The latter is M Feel Obj, Thanks M Tran
s Obj (information), M Proc Obj (opinion, opinion), M build
It is classified into Obj (design, plan, result) and Mact Obj (knowledge area, business area).

FIG. 9 is a diagram showing the main properties of the abstract existence. In the same figure, the slot S3 is a destination to which it belongs and a place where its existence exists. Slot S4
Is a related object, for example the sun against sunset. FIG. 10 is a diagram showing the structure of a business area belonging to Mact Obj.

FIG. 11 is a diagram showing the detailed structure of the structure of an organization linked at multiple levels. The slot S2 is a higher organization to which the organization belongs, and the slot S3 is a lower organization such as a department or section included in the organization. Slot S4
Is the type of organization, such as government, interest groups, academic groups, etc. Slot S5 is a business type, manufacturing,
Development, commerce, etc. This information is used as information indicating the quality of work that a person is engaged in. The slot S8 is a nominal length, S9 is a representative, and their respective job titles. The lower part of FIG. 11 is a diagram showing an example of the organization.

FIG. 12 is a diagram showing the structure and example of the knowledge area. FIG. 13 is a diagram showing an example of the hierarchical structure of the knowledge area. FIG. 14 is a diagram showing the knowledge structure under SPACE. It consists of spatial quantities such as range, distance, volume, etc. In the figure, the sub-continent is a part of the continent such as North America, South America, and Southwest Asia. What is a region? K. Then, in England, Scotland, and Japan, it is Hokkaido and Honshu (this further includes the Kanto and Kansai regions). A State is, alternatively, a county or a province.

FIG. 15A is a diagram showing the structure of a place. The slot S2 is a place included in the place, and the slot S3 is a place to which the place belongs. Slot S7
Is a geographical position, which is, for example, a latitude or longitude value.
FIG. 15 (b) is a diagram showing the structure of a country. For countries,
Slot S2 is a state and S3 is a continent. Moreover, the capital is provided as the slot S8. Furthermore, as properties other than the slot in the figure, government, daylight saving time, necessity of visa,
Current situation (developed countries, developing countries), currency, TV signal system, temperature, etc. FIG. 15 (c) is a diagram showing the structure of Japan. Further, in the case of a city, there are connections with other places (distance, direction, etc.) and tourist attractions. FIG. 16 is a diagram showing the structure of Venue.

FIG. 17 is a diagram showing a knowledge structure under a unit time. The unit time represents a concept related to time such as day and month. Time has the quality of flowing and cannot be recovered. It is also a resource. It also has the property that it can be consumed and cannot be controlled. FIG.
FIG. 3 is a diagram showing a conceptual structure of time. Slots S1, S
As shown in 2, the time division has the same inclusion relation as that of the place. FIG. 19 is a diagram showing the structure of an event, where a1) shows the structure and a2) shows the subcategories. The subcategory intensive is also
It is classified as shown in b).

FIG. 20 shows the structure under the DRIVING FORCES. These are forces that bring in a set of actions. The properties of Driving forces include type (natural or intentional), type of object (object of action, eg whole object or human only), and set of results (expected ones and other possibilities). . FIG.
As shown in 0, Driving forces, Themes, Goals-Pl
Ans and MOPS / Scenes are classified, and Themes are further classified as shown in FIG.

FIG. 22 is a diagram showing the structure of Goal-Plan. Goals-Plans is for life forms that execute a plan,
Intentiona to take action to achieve the plan
l psychological driving forces. In FIG. 22, WHO is a goal processor, and WHAT is information about the goal itself. SITUATION is the probability of choosing between normal and alternative plans, normal factors, etc. HOW is a plan to achieve the goal, and there are normal plan and alternative plan. POST
-CONDITIONS has a set of results and expected goals.

FIG. 23 is a diagram showing the structure of the MOP.
MOPS is a generalized plan used for eliminating variety of goals, and constitutes a scene to be executed in a specified order. FIG. 24 is a diagram showing the structure of a scene. A scene is a fixed set of actions that does not require planning and is executed to satisfy the main goal or the MOP to which it belongs.

FIG. 25 is a diagram showing a hierarchy of generalized goal plans under Mental Existance. Work
For Existance, according to the stage of Work, DKNOW, D
O Has three goals: WORK, PRESENT / PUBLISH. First, you have to learn about a new work (DLEARN) before you start. Even when I continue to work, I must keep up with progress in the field (DKNOW for M KEEP ABREAST). M DO WORK is the actual content of the work, and the final phase of evaluating the work result is done by the goal of Present / Publish (M GET EVALUATED).

FIG. 26 is a diagram showing a domain-dependent goal plan structure, which is applied to two domains of R & D and sales. FIG. 27 is a diagram showing basic goals. For example, DPROX is a goal to reach a specific place, and includes the goals of using a vehicle and getting a ride. FIG. 28 is a diagram showing the structure of the action. FIG. 29 is a diagram showing an example of the action. FIG.
0 is a diagram showing the structure of MEET. FIG. 31 is a diagram showing a draft instance of MEET. Figure 32 shows AGRE
It is a figure which shows the structure of EMENT. FIG. 33 shows MTRANS.
It is a figure which shows the conceptual structure of. FIG. 34 is a diagram showing a conceptual structure of PTRANS. FIG. 35 is a diagram showing a conceptual structure of PTRANS.

FIG. 36 is a diagram showing the relationship between driving forces and actions. In the figure, Int. Is Intentiona
l and psy. are psychological, and mech. is mechanical. Driving forces are the states of objects on which force acts,
It causes changes in the state of related abstract entities, as well as spatial and temporal changes.

FIG. 37 shows the status descriptor (S
It is a figure which shows the example of a (tate descriptor). The state descriptor is
Describes the state of an entity and the relationships between two or more entities. Where ACONFIG is an abstract entity,
A state descriptor of an abstract compositional relationship between an object, a result of advancing forces (adverb), or time. ESCHEDULE
Is an event scheduler that is the state descriptor of the event, LOCATE is the state descriptor of the space, MSTATE is the descriptor of the psychological state, PCONFIG is the relationship between the physical objects or the physical configuration of the object and space, and john is in Tokyo, the book is
It is a verb that covers on the table, Delhi is in India. WANT is a state descriptor of driving forces.

The processing procedure for obtaining the necessary information from the knowledge base 20 will be described below. FIG. 38 is a flowchart for knowing a specific attribute value of a certain matter. The input to the system is the knowledge structure KS1, and
Request the value of the attribute Attr1 as output (step S44)
1). First, using the knowledge about the knowledge structure of the knowledge base 20, it is checked from which (which slot) of the knowledge structure KS1 the value of the attribute Attr1 can be obtained (step S44).
2). If a slot is found, the attribute Attr from it
A value of 1 is obtained and returned to the request source (steps S443-4).
If no slot is found, an error message is returned (step S445). As a specific example, FIG. 39 is a flowchart when the knowledge structure P1 of a person is input and the age is requested. As shown in FIG. 7, since the age is in the slot S2, the value of the slot S2 is searched and output.

FIG. 40 is a flowchart for referring to another knowledge structure based on the given knowledge structure. Here, it is a flow chart when the knowledge structure P1 of the same person as above is input and an organization is requested. As shown in FIG. 7, since the organization is in the slot S7 and the value of the slot S7 is a pointer to the knowledge structure Org1 of the organization, this knowledge structure Org1 is searched and output.

FIG. 41 is a flowchart for referring to the attribute of another knowledge structure based on the given knowledge structure. Here, the knowledge structure P of the same person as above
6 is a flowchart when 1 is input and the location of the organization to which a person belongs is requested. As shown in FIG. 7, the organization is in slot S7, and the value of slot S7 is the knowledge structure of the organization.
This knowledge structure Org1 is searched because it is a pointer to Org1. As shown in FIG. 11, in the knowledge structure of the organization,
The location is in slot S7, the slot S of knowledge structure Org1
Since the value of 7 is a pointer to V2's knowledge structure V2,
This knowledge structure V2 is searched and output.

FIG. 42 is a flow chart for knowing a higher-level structure common to two or more knowledge structures. The input to the system is the knowledge structures KS1 and KS2, and the output requires a higher-level structure that commonly overlaps the knowledge structures KS1 and KS2 (step S481). First, using the knowledge about the knowledge structure of the knowledge base 20, the “belongs to” slot in each of the knowledge structures KS1 and KS2 is obtained, and the value is used to fetch into the parent knowledge structure. Similarly, fetch the child structure using the "owns" slot. Then, the matching of the structures related to the knowledge structures KS1 and KS2 is checked to find the upper structure to be shared (step S482). If a common structure is found, the structure is obtained and returned to the request source (step S
483-4). If no common structure is found, an error message is returned (step S485).

As a concrete example, FIG. 43 is a flow chart in the case where the knowledge structures P1 and P2 of a place are input and a common upper structure is requested. The place has a hierarchical structure as shown in FIG. 44. By tracing the "belongs to" slot and the "owns" slot, a common upper structure P3 is obtained and output.

As mentioned above, "belongs to" slot and "o"
The knowledge structure with wns "slots allows us to identify higher-level structures that are common to the knowledge structures in the two places. It also helps in applying the sentence creation rule according to the perspective of the question and answer. Also, for questions such as the question and answer example shown in FIG. By specifying the positional relationship, a response as shown in the figure becomes possible.

FIG. 46 is another specific example for obtaining a higher-level structure common to two knowledge structures, two knowledge areas KD.
2 is a flowchart of a process for obtaining a higher-level structure common to 1 and KD2. The knowledge area has a hierarchical structure as shown in FIG. 13, and by tracing the "belongs to" slot and the "owns" slot, the knowledge area KD2 itself is eventually obtained and output as a common upper structure.

As described above, "belongs to" slot and "o"
The knowledge structure with wns "slots allows us to identify higher-level structures that are common to the knowledge structures of the two knowledge domains. So, for example, in a letter writing system, you can When introducing, the degree of detail of explanation can be determined from the result of comparing one's work and the other's work.If the common knowledge domain is a very high hierarchy, the commonality of both Since it is small, it is judged that the other person cannot understand even if the detailed explanation is given.On the other hand, when the two are very close to each other, explaining the work content can be important for attracting the interest of the other person. If the content of work is similar, an abbreviation is sufficient when expressing the name of a thing related to it, for example, the name of a meeting.

Similarly, the examination of a higher-level structure that is common to the knowledge structure of an organization is, for example, for two persons belonging to the same large company, to determine in which hierarchy the organizations to which they belong are different. You can

For the question "What is a jounal?", According to the classification of knowledge as shown in FIG. 5, "Journal i
sa type of written material which is periodical a
nd deals with one specialized knowledge domain. "
Can be answered.

Also, for example, in the example described with reference to FIG. 41, if the slot of the knowledge structure of Venue (see FIG. 16) is a pointer to another structure as shown in FIG. 47, point to it. It is also possible to refer to the upper and lower structures based on the values of the "belongs to" slot and the "owns" slot, as well as referencing the existing structure.

As long as the functions of the present invention are executed, the processing is performed by supplying a program to the device or the system, whether it is a single device or a system composed of a plurality of devices. Needless to say, the present invention is applied even in such cases.

[0047]

As described above, according to the present invention,
When obtaining the value of a specific attribute of an item, the knowledge base also refers to the knowledge of other items related to the item. You can search for richer information by using unwritten knowledge. Moreover, this search can supplement the information lacking in the knowledge of a specific matter from the knowledge of other matters.

Further, since it is possible to know a common upper item for a plurality of items, it is possible to determine the relationship between them based on this.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a hardware configuration of a natural language processing device according to an embodiment.

FIG. 2 is a diagram showing a structure of a knowledge base.

FIG. 3 is a diagram showing the contents of a knowledge base of general knowledge.

FIG. 4 is a diagram showing a conceptual configuration of an object.

FIG. 5 is a diagram showing a knowledge structure existing under an object.

FIG. 6 is a diagram showing a configuration of a written object.

FIG. 7 is a diagram showing a structure of a person and an example thereof.

FIG. 8 is a diagram showing a structure existing under an abstract existence.

FIG. 9 is a diagram showing properties of abstract existence.

FIG. 10 is a diagram showing a structure of a work area.

FIG. 11 is a diagram showing a structure of an organization and an example thereof.

FIG. 12 is a diagram showing a configuration and an example of a knowledge area.

FIG. 13 is a diagram showing an example of a hierarchical structure of a knowledge area.

FIG. 14 is a diagram showing the knowledge structure under SPACE.

FIG. 15 is a diagram showing a SPACE and country knowledge structure.

FIG. 16 is a diagram showing the structure of Venue.

FIG. 17 is a diagram showing a knowledge structure under a unit time.

FIG. 18 is a diagram showing a conceptual structure of time.

FIG. 19 is a diagram showing the structure of an event.

FIG. 20 is a diagram showing the knowledge structure under DRIVING FORCES and Themes.

FIG. 21 is a diagram showing classification of Themes.

FIG. 22 is a diagram showing the structure of Goal-Plan.

FIG. 23 is a diagram showing a structure of MOP.

FIG. 24 is a diagram showing a structure of a scene.

FIG. 25 is a diagram showing a hierarchy of a generalized goal plan.

FIG. 26 is a diagram showing a structure of a domain-dependent goal plan.

FIG. 27 is a diagram showing a basic goal.

FIG. 28 is a diagram showing a structure of an action.

FIG. 29 is a diagram showing an example of an action.

FIG. 30 is a diagram showing a structure of MEET.

FIG. 31 is a diagram showing a draft instance of MEET.

FIG. 32 is a diagram showing a structure of AGREEMENT.

FIG. 33 is a diagram showing the structure of MTRANS.

FIG. 34 is a diagram showing a structure of PTRANS.

FIG. 35 is a diagram showing a structure of PTRANS.

FIG. 36 is a diagram showing the relationship between Driving forces and actions.

FIG. 37 is a diagram showing an example of a state descriptor which is the result of an action.

FIG. 38 is a flowchart for knowing a specific attribute value of a certain matter.

[Fig. 39] Fig. 39 is a flowchart of a process for obtaining an age from the knowledge structure of a person.

FIG. 40 is a flowchart of a process of searching by referring to another knowledge structure based on the given knowledge structure.

FIG. 41 is a flowchart of processing for obtaining the location of an organization to which a person belongs based on the knowledge structure of the person.

FIG. 42 is a flowchart of processing for obtaining a higher-level structure that is common to two or more knowledge structures.

FIG. 43 is a flowchart of a process of obtaining a higher-level structure having a common knowledge structure of two or more places.

FIG. 44 is a diagram showing a hierarchical structure of places.

FIG. 45 is a diagram showing an example of a question and answer regarding a place.

FIG. 46 is a flowchart of processing for obtaining a higher-level structure common to two knowledge areas.

FIG. 47 is a diagram showing a relationship between a certain Venue knowledge structure and another knowledge structure.

[Explanation of symbols]

 1 Input Unit 2 CPU 3 Output Unit 4 Program Memory 5 Data Memory 6 Bus 20 Knowledge Base

Claims (18)

[Claims] 1. A knowledge base for storing, as knowledge, values of a plurality of predetermined attributes of each item, categories of each item, and interrelationships between a plurality of categories, designating means for designating the items and attributes, and the designating means. With reference to the reading means for reading out the value of the specified attribute of the item specified by, from the knowledge base, and the mutual relationship stored in the knowledge base,
An information processing system comprising: control means for controlling the reading means so as to read knowledge of other matters related to the value read by the reading means. 2. The information processing system according to claim 1, wherein the control unit controls the reading unit to read a value of a specific attribute of knowledge of the other matter. 3. The plurality of predetermined attributes are defined for each concept to which each item belongs.
The information processing system as described. 4. The information processing system according to claim 1, wherein the mutual relationship is a pointer to another knowledge stored as a value of an attribute. 5. A knowledge base for storing, as knowledge, the values of a plurality of predetermined attributes of each item, the category of each item, and the interrelationship between the categories, a specifying unit for specifying a plurality of items, and the specifying unit. With respect to each of the plurality of items designated by, the reading unit that reads the knowledge about the related item from the knowledge base with reference to the mutual relationship, and the determination that determines the common part of the knowledge read by the reading unit means. An information processing system, comprising: 6. The information processing system according to claim 5, wherein the determination unit determines a common upper item for the plurality of items. 7. The predetermined plurality of attributes are defined for each concept to which each item belongs.
The information processing system as described. 8. The information processing system according to claim 5, wherein the mutual relationship is a pointer to another knowledge stored as a value of an attribute. 9. The information processing system according to claim 5, wherein as one of the predetermined plurality of attributes, identification information of a higher or lower item of the item is included. 10. A specification step of specifying an item and an attribute, and a value of a specified attribute of the item specified by the specification step, a value of a plurality of predetermined attributes of each item, a category of each item and a plurality of items. A reading step of reading from a knowledge base that stores the mutual relation between categories as knowledge, and referring to the mutual relation stored in the knowledge base,
An information processing method, comprising: a control step of controlling the reading step so as to read knowledge of other matters related to the value read by the reading step. 11. The information processing method according to claim 10, wherein the control step controls the reading step so as to read a value of a specific attribute of knowledge of the other matter. 12. The information processing method according to claim 10, wherein the predetermined plurality of attributes are determined for each concept to which each item belongs. 13. The information processing method according to claim 10, wherein the mutual relationship is a pointer to another knowledge stored as an attribute value. 14. A designation step of designating a plurality of items, and a plurality of predetermined attribute values of each item, a category of each item, and a plurality of categories for each of the plurality of items designated by the designation step. A reading step of reading knowledge about related matters from the knowledge base by referring to the mutual relationship of a knowledge base that stores the mutual relationship as knowledge, and a determining step of determining a common part of the knowledge read by the reading step. . An information processing method characterized by the above. 15. The information processing method according to claim 14, wherein the determination step determines a common upper item for the plurality of items. 16. The information processing method according to claim 14, wherein the predetermined plurality of attributes are defined for each concept to which each item belongs. 17. The information processing method according to claim 14, wherein the mutual relationship is a pointer to other knowledge stored as an attribute value. 18. As one of the predetermined plurality of attributes,
15. The information processing method according to claim 14, wherein the information includes identification information of higher or lower items of the item.